Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
An Algorithm for Total Variation Minimization and Applications
Journal of Mathematical Imaging and Vision
Split Bregman Algorithm, Douglas-Rachford Splitting and Frame Shrinkage
SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
Anisotropic Smoothing Using Double Orientations
SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
Duality-based algorithms for total-variation-regularized image restoration
Computational Optimization and Applications
Partition into almost straight trails
Discrete Applied Mathematics
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Total variation minimisation is a well-established method for digital image restoration. Its implicit preservation of edges permits the derivation of anisotropic models for a qualitative improvement at corners. This paper is a synopsis of anisotropic models with state-of-the-art insights into the numerics of isotropic models. We generalise two representative models from both branches of research. This formulation leads to a general convergent algorithm and a general highly efficient algorithm which apply for both cases. A transfer of the discretisation from the anisotropic model to the isotropic setting results in an improvement of rotational invariance.